Additive and Multiplicative Uncertainty Revisited: What Explains the Contrasting Biases?

above the certainty level while for additive uncertainty the price should be lower than the certainty level. This note gives an intuitive explanation for the result after first presenting a parsimonious review of the two models. We also discuss which, if either, of the two models is more realistic. Received December 14, 2001; revised version received July 16, 2002 Published online: April 30, 2003 We thank referees for helpful comments. Ciaran Driver would like to acknowledge the research facilities from ANU, Canberra for their help in writing this paper.     

Service Competitiveness – An Anglo-US Study

This article reports on the latest in a series of international comparisons of management practices and performance outcomes of industries in various countries. Here, it is the service industries in the UK and the US which come under the microscope. Among the companies surveyed, there were more world-class performers in the US than the UK, but also more low performers. The concluding part of the article is diagnostic – the authors also suggest measures which could improve performance.     

Auctioning the Airwaves: The Contest for Broadband pcs Spectrum

The House and Senate of the United States Congress recently passed legislation that directs the FCC to establish a system for using auctions to allocate the use of radio spectrum for personal communications services. There is a unique and unprecedented set of issues that arise in this context, which are of interest to economists, industry analysts, regulators, and policymakers. We discuss these issues and evaluate their likely impact on the outcome of the spectrum auctions. In addition, we argue that there may be pitfalls in the auction procedure adopted by the FCC, and we discuss possible alternative procedures.     

THE LOCATION OF NONMETROPOLITAN HIGH-TECH INDUSTRIES: A Comparison of Regional Determinants

A study of the location of three classifications of high-tech industries in rural areas was undertaken using ordinary least squares, Tobit, and a two-step estimation procedure suggested by Heckman (1976). The results indicate that the location decision for high tech firms is influenced primarily by the county population, adjacency to an SMSA, and the expenditures on public infrastructure (exclusive of education expenditures). However, location near interstate highways was generally not a significant factor. Results were similar between branch and unit (single ownership) plants. Some differences in signs of orders of magnitude occurred among the estimation procedures. Making a choice between Tobit and Heckman approaches depends upon the goal of the research.